Evaluating an Additive Manufactured Acoustic Metamaterial Using the Advanced Noise Control Fan
Bibliographic record
Abstract
This paper examines the performance of a 3D printed acoustic metamaterial as an acoustic treatment for aircraft engine nacelles in the Advanced Noise Control Fan. As the level of air travel continues to increase, so too does the demand for better noise-reduction technologies for aircraft. Engines are one of the two main sources of noise generated by aircraft, with fan noise, in particular, being of concern due to its broadband and tonal contributions. Small and lightweight methods of addressing both broadband and tonal noise are necessary due to the limitations presented by the current engine design. Presented in this paper is a novel acoustic metamaterial that has undergone design optimization for broadband noise reduction. The final design was produced using 3D printing and tested using the Advanced Noise Control Fan at the University of Notre Dame. It was found that the material is capable of reducing the first harmonic of the blade passing frequency by up to 18.5 dB, with an overall noise reduction of 3.7 dB.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".